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8/12/2019 optimizationheuristicsslideshare-130201014236-phpapp01

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A presentation on

Optimization Heuristicsby

Kausal Malladi(Student, IIIT Bangalore)


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Agenda

Definition of a Heuristic

Optimizationheuristics

Genetic Algoriths !ill "libing

Tabu Search

Siulated Annealing

S#ar Intelligence

$ith e%aple applications


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Heuristic

&%perience based techni'ues for problesoling, learning and discoery *Adopted fro$i+ipedia

Different types -ule of thub

"oon sense

&ducated Guess Meta.heuristics/ 0araeters that influence

eploying a heuristic


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Optimization Heuristics

Al#ays difficult to sole NP-Hard and NP-Completecoputational probles

&en #ith different optii1ation techni'ues,actual running tie is neer guaranteed

$e eploy soe rules 2 results based one%perients to state that a near.optial

solution can be obtained 3o proof as to #hy and ho# #e get

solution


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Local Search

To solehard4ptii1ation probles

Search Space / Doain of function to beoptii1ed

5inding a solution aong nuber ofcandidate solutions, a%ii1ing a criterion

Sub.failies/

!ill "libing

Tabu Search

Siulated Annealing


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Hill Climbing

Iterativealgorith, starts #ith arbitrarysolution

6oo+s for bettersolutions increentally

-epeats until no further iproeents

Good for finding a local optimum

Doesn7t guarantee global optimum Siple, popular

$or+s #ell, generally


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Hill Climbing

0opular e%aple 8 TS0

Traelling Salesan 0roble

Kno#n NP-Hardproble

Initial solution ay not be optial

Shorter route is ore li+ely to be obtained

$idely used in Artificial Intelligence

Significant results in real.tie systes Any-timealgorith

0itfall/ 0lateau


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Tabu Search

Iteratiely proceeds fro one potentialsolution S to an iproed one S in theneighbourhood of S

4ercoes fe# pitfalls of other LocalSearchtechni'ues (&%aple/ Plateau)

9isited solutions ar+ed !tabu"

Search progresses using #emor$Structures

4ften a benchar+ heuristic:


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Tabu Search

Meory structures

Describe

9isited solutions

;ser proided sets of rules

"ategories

Short ter

Interediate ter 6ong ter

5or tabu list


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Tabu Search

Issues

4nly effectie in discrete search spaces

$or+around/ A similarity measure

!igh diensional search space

$or+around/ "reate a tabu list consistingof attributes of a solution

"an be ore effectie solution, has

probles tooAspiration criteriaintroduced

4erride solution7s tabu state


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Tabu Search

"oon e%aple 8 TS0


Tabu Search finds a satisficing solution

Starts #ith an initial solution that can befound randoly or using soe algorith

4rder in #hich t#o cities are isited, iss#apped

Total traelling distance is the etric A acceptable solution added to tabu list if

in neighbourhood of accepted solution


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Simulated Annealing

Inspiration/ Annealingin Metallurgy

0robabilistic eta.heuristic

Appro%iates global optimum in a largesearch space

Gies acceptably good solution if not thebest

Slo# decrease in probability of accepting#orse solutions


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Simulated Annealing

&%aple 8 TS0


Metric under consideration is Mileage

#etropolis Algorithm

0air#ise changing order of isit to cities

Solutions that don7t lo#er ileage alsoaccepted

e.D/T

> R(0,1) D is the change of distance iplied

If T is large, any bad choices are ade


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S%arm &ntelligence

A collectie behaior of self.organi1edsystes #hich are decentrali1ed *Adopted fro$i+ipedia

"an7t predict ho# the systes behaeeen #ithout a centrali1ed control

$idely eployed inArtiicial Intelligence

&%aple Ant "olony 4ptii1ation

3atural ants Siulation agents

0heroones -ecording position, 'uality


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'e(erences

http/22###iaengorg2publication2$"&2$"&?pp@.@pdf(Gae Theory using Genetic Algoriths)

http/22ath#orld#olfraco2SiulatedAnnealinghtl(Siulated Annealing)

http/22artificialintelligence.notesblogspotin22hill.clibing.procedureht

(!ill "libing in Artificial Intelligence)
http://www.iaeng.org/publication/WCE2007/WCE2007_pp61-64.pdfhttp://mathworld.wolfram.com/SimulatedAnnealing.htmlhttp://artificialintelligence-notes.blogspot.in/2010/07/hill-climbing-procedure.htmlhttp://artificialintelligence-notes.blogspot.in/2010/07/hill-climbing-procedure.htmlhttp://mathworld.wolfram.com/SimulatedAnnealing.htmlhttp://www.iaeng.org/publication/WCE2007/WCE2007_pp61-64.pdf


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